Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors. With Kornia we fill the gap between classical and deep computer vision that implements standard and advanced vision algorithms for AI. Our libraries and initiatives are always according to the community needs.

Features

  • Differentiable Computer Vision library, with strong GPU support
  • Module to perform data augmentation in the GPU
  • Set of routines to perform color space conversions
  • Module to perform normalization and intensity transformation
  • Geometric computer vision library to perform image transformations, 3D linear algebra and conversions using different camera models
  • Image to tensor utilities and metrics for vision problems

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License

Apache License V2.0

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Additional Project Details

Operating Systems

Linux, Windows

Programming Language

Python

Related Categories

Python Libraries, Python Machine Learning Software, Python Computer Vision Libraries, Python Image Processing Software, Python Image Processing Libraries

Registered

2022-08-01